Recordings from Bits & Bites 2024

Learn at your own pace with recordings from our 10-part Bits & Bites 2024 series, now available for purchase. Choose the topics that interest you and customize your learning experience.

For more information:
Email: Jeannette Martins jmartins@ucdavis.edu
Phone: +1-530-754-5357

Bits & Bites 2024 10-Part Series

  • Bits & Bites #1: Mastering Lipidomics: From Biology to Advanced Techniques with Dr. Tong Shen, UC Davis

    • Required Software: None
    • Participant prerequisites: None
    • Level: Introductory
    • Short description of the course: In this short course, our focus will be on lipidomics, where we'll cover systems-level lipid analysis through practical case studies. We’ll explore mass spectrometry-based lipid analysis, covering advanced separation techniques and emerging technologies. Throughout, we’ll provide best practices for the entire experimental pipeline—from crafting experimental designs and sample extraction to emphasizing the crucial role of quality control. This ensures the reliability and accuracy of your lipidomics research, offering a practical and comprehensive learning experience.
       

  • Bits & Bites #2: Mass Spectrometry for Metabolomics with Dr. Uri Keshet, UC Davis

    • Required Software: None
    • Participant prerequisites: None
    • Level: Introductory
    • Short description of the course: Mass spectrometry (MS) has a crucial role in metabolomics as it’s one of the most widely used analytical techniques in the field. In this comprehensive yet short course, we will cover various MS systems and models like TOF, QQQ, and Orbitrap, understanding their application in metabolomics. You’ll also learn how to make informed decisions when selecting the right MS instrument, method, and parameters tailored to your research needs. Lastly, you’ll gain practical insights on how to optimize your workflow with tips and tricks for developing high-throughput MS methods, such as a short 5-minute method, designed for practical use in metabolomics research.
       

  • Bits & Bites #3: Mass Spectrometry Imaging 101: Sample Preparation with Dr. Elizabeth Neumann, UC Davis

    • Required Software: None
    • Participant prerequisites: None
    • Level: Introductory
    • Short description of the course: Beginning your mass spectrometry imaging research project starts with mastering sample preparation techniques such as tissue freezing and sectioning, matrix application, data analysis, and data visualization. In this short course, we will provide a comprehensive overview of mass spectrometry imaging, covering sample preparation methods, instrumentation, data analysis techniques, and practical guidance to kick-start your research project. 
       

  • Bits & Bites #4: Quantification in Metabolomics: Tools for Robustness and Accuracy with Dr. Huaxu Yu, UC Davis

    • Required Software: None
    • Participant prerequisites: None
    • Level: Introductory
    • Short description of the course: Metabolomics, renowned for its broad, untargeted exploration of metabolites, holds immense value. Yet, targeted metabolomics and precise quantification are equally vital. Professionals across fields like pharmacology and medicine heavily depend on accurate quantification. This short course focuses on classical quantitation within targeted metabolomics, focusing on critical aspects like selectivity, accuracy, and LOD/LOQ. We'll navigate challenges like dealing with adducts and in-source fragmentation. Additionally, we’ll discuss the nuances between targeted and untargeted metabolomics, shedding light on essential concepts such as normalization techniques and what to consider when doing one or the other.
       

  • Bits & Bites #5: Using MS-DIAL to get accurate comprehensive LC-MS/MS metabolomics datasets with Dr. Jake Folz, ETH Zurich

    • Required Software: MS-DIAL for Windows. Versions of the tool to be used will be announced closer to the course date.
    • Participant prerequisites: Basic understanding of LC-MS and understanding of how MS/MS spectra are used in metabolite identification.
    • Level: Intermediate
    • Short description of the course: Metabolomics demands meticulous data processing, especially with large complex datasets (i.e., 1000s of samples, different shipping batches, longitudinal studies). Using hands-on examples, we will provide best practices on how to perform fine-tuned curation of LC-MS/MS data generated through MS-DIAL a freely-available data processing tool for untargeted metabolomics data and other tips for quality assessment and reducing unknown features to ensure accuracy.
       

  • Bits & Bites #6: Using the GNPS for Metabolomics Data Analysis and Visualizations with Dr. Mingxun Wang, UC Riverside

    • Required Software: None
    • Participant prerequisites: GNPS Account, no programming experience necessary.
    • Level: Intermediate
    • Short description of the course: In this short course, we will get familiar with GNPS (Global Natural Products Social Molecular Networking) a web-based mass spectrometry ecosystem, and learn how to look at your data using classical molecular networking. Explore GNPS Tools for MassIVE data navigation, including classical molecular networking, data selection, mastering molecular network workflows, interactive LC/MS visualization, and compound identification. Uncover insights into intricate mass spectrometry data efficiently. Exciting material to be covered with new additions to GNPS, that will be launched in the Wang Lab in 2024.
       

  • Bits & Bites #7: Using MetaboAnalyst for Metabolomics Statistics and Data Visualizations with Dr. Jeff Xia, McGill University

    • Required Software: Laptop with stable internet connection
    • Participant prerequisites: Basic knowledge of computer skills. No programming experience is necessary.
    • Level: Introductory
    • Short description of the course: In this short course, we will focus on mastering MetaboAnalyst 5.0, the robust platform for statistical analysis in metabolomics. Learn data input, preprocessing, and key analyses like PCA, PLS-DA, and OPLS-DA. Explore functional analysis techniques, and biomarker identification, and tackle complex metadata for robust statistical insights in metabolomics data.
       

  • Bits & Bites #8: Statistics in R for Metabolomics with Dr. Christopher Brydges

    • Required Software: R and RStudio (Exact versions to be specified nearer the course date)
    • Participant prerequisites: Basic knowledge of statistics (i.e., what a t-test is and when to use one)
    • Level: Intermediate
    • Short description of the course: In this short course, we will focus on analyzing case/control study data and crafting compelling data visualizations in R. Explore R's core concepts, master data loading, and manipulation including missing data imputation. Learn essential data analysis techniques like univariate vs. multivariate approaches and delve into creating and customizing impactful graphs and plots. Elevate your R skills and transform your data with us!
       

  • Bits & Bites #9: Biochemical interpretation and visualization of metabolomics data with Dr. Oliver Fiehn, UC Davis

    • Required Software: None
    • Participant prerequisites: None
    • Level: Introductory
    • Short description of the course: What do you do after you have completed statistics? How do you map and visualize your data? This short course will focus on helping you interpret data, generate hypotheses, integrate biological and metabolomics data, and make the most of freely available online databases. We will provide practical tips on curation, data mapping, and visualization.
       

  • Bits & Bites #10: Identification of unknown compounds in untargeted metabolomics using freely available software with Dr. Arpana Vaniya, UC Davis

    • Required Software:
    • Participant prerequisites: Basic knowledge of computer skills. No programming experience is necessary.
    • Level: Introductory
    • Short description of the course: Where do you start when a multitude of approaches exist to address the challenge of metabolite identification? There are so many options from mass spectral library searches, in silico fragmentation tools, and database searching. We will provide tips on how to explore the landscape of compound identification, leverage in silco fragmentation tools, and gain valuable hands-on experience by using real-world challenges.